Genome-wide genotype and sequence-based reconstruction of the 140,000 year history of modern human ancestry.
Ontology highlight
ABSTRACT:
SUBMITTER: Shriner D
PROVIDER: S-EPMC4131216 | biostudies-literature | 2014 Aug
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:We present the high-quality genome sequence of a ∼45,000-year-old modern human male from Siberia. This individual derives from a population that lived before-or simultaneously with-the separation of the populations in western and eastern Eurasia and carries a similar amount of Neanderthal ancestry as present-day Eurasians. However, the genomic segments of Neanderthal ancestry are substantially longer than those observed in present-day individuals, indicating that Neanderthal gene flow into the ancestors of this individual occurred 7,000-13,000 years before he lived. We estimate an autosomal mutation rate of 0.4 × 10(-9) to 0.6 × 10(-9) per site per year, a Y chromosomal mutation rate of 0.7 × 10(-9) to 0.9 × 10(-9) per site per year based on the additional substitutions that have occurred in present-day non-Africans compared to this genome, and a mitochondrial mutation rate of 1.8 × 10(-8) to 3.2 × 10(-8) per site per year based on the age of the bone.
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Project description:We present a general hidden Markov model framework called R: econstructing A: ncestry B: locks BIT: by bit (RABBIT) for reconstructing genome ancestry blocks from single-nucleotide polymorphism (SNP) array data, a required step for quantitative trait locus (QTL) mapping. The framework can be applied to a wide range of mapping populations such as the Arabidopsis multiparent advanced generation intercross (MAGIC), the mouse Collaborative Cross (CC), and the diversity outcross (DO) for both autosomes and X chromosomes if they exist. The model underlying RABBIT accounts for the joint pattern of recombination breakpoints between two homologous chromosomes and missing data and allelic typing errors in the genotype data of both sampled individuals and founders. Studies on simulated data of the MAGIC and the CC and real data of the MAGIC, the DO, and the CC demonstrate that RABBIT is more robust and accurate in reconstructing recombination bin maps than some commonly used methods.
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Project description:The transatlantic slave trade was the largest forced migration in world history. However, the origins of the enslaved Africans and their admixture dynamics remain unclear. To investigate the demographic history of African-descendant Marron populations, we generated genome-wide data (4.3 million markers) from 107 individuals from three African-descendant populations in South America, as well as 124 individuals from six west African populations. Throughout the Americas, thousands of enslaved Africans managed to escape captivity and establish lasting communities, such as the Noir Marron. We find that this population has the highest proportion of African ancestry (?98%) of any African-descendant population analyzed to date, presumably because of centuries of genetic isolation. By contrast, African-descendant populations in Brazil and Colombia harbor substantially more European and Native American ancestry as a result of their complex admixture histories. Using ancestry tract-length analysis, we detect different dates for the European admixture events in the African-Colombian (1749 CE; confidence interval [CI]: 1737-1764) and African-Brazilian (1796 CE; CI: 1789-1804) populations in our dataset, consistent with the historically attested earlier influx of Africans into Colombia. Furthermore, we find evidence for sex-specific admixture patterns, resulting from predominantly European paternal gene flow. Finally, we detect strong genetic links between the African-descendant populations and specific source populations in Africa on the basis of haplotype sharing patterns. Although the Noir Marron and African-Colombians show stronger affinities with African populations from the Bight of Benin and the Gold Coast, the African-Brazilian population from Rio de Janeiro has greater genetic affinity with Bantu-speaking populations from the Bight of Biafra and west central Africa.
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Project description:Identification of protein quantitative trait loci (pQTL) helps understand the underlying mechanisms of diseases and discover promising targets for pharmacological intervention. For most important class of drug targets, genetic evidence needs to be generalizable to diverse populations. Given that the majority of the previous studies were conducted in European ancestry populations, little is known about the protein-associated genetic variants in East Asians. Based on data-independent acquisition mass spectrometry technique, we conduct genome-wide association analyses for 304 unique proteins in 2,958 Han Chinese participants. We identify 195 genetic variant-protein associations. Colocalization and Mendelian randomization analyses highlight 60 gene-protein-phenotype associations, 45 of which (75%) have not been prioritized in Europeans previously. Further cross-ancestry analyses uncover key proteins that contributed to the differences in the obesity-induced diabetes and coronary artery disease susceptibility. These findings provide novel druggable proteins as well as a unique resource for the trans-ancestry evaluation of protein-targeted drug discovery.
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Project description:BackgroundGenetic data are known to harbor information about human demographics, and genotyping data are commonly used for capturing ancestry information by leveraging genome-wide differences between populations. In contrast, it is not clear to what extent population structure is captured by whole-genome DNA methylation data.ResultsWe demonstrate, using three large-cohort 450K methylation array data sets, that ancestry information signal is mirrored in genome-wide DNA methylation data and that it can be further isolated more effectively by leveraging the correlation structure of CpGs with cis-located SNPs. Based on these insights, we propose a method, EPISTRUCTURE, for the inference of ancestry from methylation data, without the need for genotype data.ConclusionsEPISTRUCTURE can be used to infer ancestry information of individuals based on their methylation data in the absence of corresponding genetic data. Although genetic data are often collected in epigenetic studies of large cohorts, these are typically not made publicly available, making the application of EPISTRUCTURE especially useful for anyone working on public data. Implementation of EPISTRUCTURE is available in GLINT, our recently released toolset for DNA methylation analysis at: http://glint-epigenetics.readthedocs.io.
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Project description:The Tibetan Plateau (TP) is considered to be one of the last terrestrial environments conquered by the anatomically modern human. Understanding of the genetic background of highland Tibetans plays a pivotal role in archeology, anthropology, genetics, and forensic investigations. Here, we genotyped 22 forensic genetic markers in 1,089 Tibetans residing in Nagqu Prefecture and collected 1,233,013 single nucleotide polymorphisms (SNPs) in the highland East Asians (Sherpa and Tibetan) from the Simons Genome Diversity Project and ancient Tibetans from Nepal and Neolithic farmers from northeastern Qinghai-Tibetan Plateau from public databases. We subsequently merged our two datasets with other worldwide reference populations or eastern ancient Eurasians to gain new insights into the genetic diversity, population movements, and admixtures of high-altitude East Asians via comprehensive population genetic statistical tools [principal component analysis (PCA), multidimensional scaling plot (MDS), STRUCTURE/ADMIXTURE, f3 , f4 , qpWave/qpAdm, and qpGraph]. Besides, we also explored their forensic characteristics and extended the Chinese National Database based on STR data. We identified 231 alleles with the corresponding allele frequencies spanning from 0.0005 to 0.5624 in the forensic low-density dataset, in which the combined powers of discrimination and the probability of exclusion were 1-1.22E-24 and 0.999999998, respectively. Additionally, comprehensive population comparisons in our low-density data among 57 worldwide populations via the Nei's genetic distance, PCA, MDS, NJ tree, and STRUCTURE analysis indicated that the highland Tibeto-Burman speakers kept the close genetic relationship with ethnically close populations. Findings from the 1240K high-density dataset not only confirmed the close genetic connection between modern Highlanders, Nepal ancients (Samdzong, Mebrak, and Chokhopani), and the upper Yellow River Qijia people, suggesting the northeastern edge of the TP served as a geographical corridor for ancient population migrations and interactions between highland and lowland regions, but also evidenced that late Neolithic farmers permanently colonized into the TP by adopting cold-tolerant barley agriculture that was mediated via the acculturation of idea via the millet farmer and not via the movement of barley agriculturalist as no obvious western Eurasian admixture signals were identified in our analyzed modern and ancient populations. Besides, results from the qpAdm-based admixture proportion estimation and qpGraph-based phylogenetic relationship reconstruction consistently demonstrated that all ancient and modern highland East Asians harbored and shared the deeply diverged Onge/Hoabinhian-related eastern Eurasian lineage, suggesting a common Paleolithic genetic legacy existed in high-altitude East Asians as the first layer of their gene pool.
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Project description:Migrations to the new world brought together individuals from Europe, Africa and the Americans. Inter-mating between these migrant and indigenous populations led to the subsequent formation of new admixed populations, such as African and Latino Americans. These unprecedented events brought together genomes that had evolved independently on different continents for tens of thousands of years and presented new environmental challenges for the indigenous and migrant populations, as well as their offspring. These circumstances provided novel opportunities for natural selection to occur that could be reflected in deviations at specific locations from the genome-wide ancestry distribution. Here we present an analysis examining European, Native American and African ancestry based on 284 microsatellite markers in a study of Mexican Americans from the Family Blood Pressure Program. We identified two genomic regions where there was a significant decrement in African ancestry (at 2p25.1, p < 10(-8) and 9p24.1, p < 2 x 10(-5)) and one region with a significant increase in European ancestry (at 1p33, p < 2 x 10(-5)). These locations may harbor genes that have been subjected to natural selection after the ancestral mixing giving rise to Mexicans.
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Project description:Historical genetic links among similar populations can be difficult to establish. Identity by descent (IBD) analyses find genomic blocks that represent direct genealogical relationships among individuals. However, this method has rarely been applied to ancient genomes because IBD stretches are progressively fragmented by recombination and thus not recognizable after few tens of generations. To explore such genealogical relationships, we estimated long IBD blocks among modern Europeans, generating networks to uncover the genetic structures. We found that Basques, Sardinians, Icelanders and Orcadians form, each of them, highly intraconnected sub-clusters in a European network, indicating dense genealogical links within small, isolated populations. We also exposed individual genealogical links -such as the connection between one Basque and one Icelandic individual- that cannot be uncovered with other, widely used population genetics methods such as PCA or ADMIXTURE. Moreover, using ancient DNA technology we sequenced a Late Medieval individual (Barcelona, Spain) to high genomic coverage and identified IBD blocks shared between her and modern Europeans. The Medieval IBD blocks are statistically overrepresented only in modern Spaniards, which is the geographically closest population. This approach can be used to produce a fine-scale reflection of shared ancestry across different populations of the world, offering a direct genetic link from the past to the present.
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Project description:BackgroundPopulation stratification can cause spurious associations in a genome-wide association study (GWAS), and occurs when differences in allele frequencies of single nucleotide polymorphisms (SNPs) are due to ancestral differences between cases and controls rather than the trait of interest. Principal components analysis (PCA) is the established approach to detect population substructure using genome-wide data and to adjust the genetic association for stratification by including the top principal components in the analysis. An alternative solution is genetic matching of cases and controls that requires, however, well defined population strata for appropriate selection of cases and controls.ResultsWe developed a novel algorithm to cluster individuals into groups with similar ancestral backgrounds based on the principal components computed by PCA. We demonstrate the effectiveness of our algorithm in real and simulated data, and show that matching cases and controls using the clusters assigned by the algorithm substantially reduces population stratification bias. Through simulation we show that the power of our method is higher than adjustment for PCs in certain situations.ConclusionsIn addition to reducing population stratification bias and improving power, matching creates a clean dataset free of population stratification which can then be used to build prediction models without including variables to adjust for ancestry. The cluster assignments also allow for the estimation of genetic heterogeneity by examining cluster specific effects.
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Project description:BackgroundAsthma exacerbations are a serious public health concern due to high healthcare resource utilization, work/school productivity loss, impact on quality of life, and risk of mortality. The genetic basis of asthma exacerbations has been studied in several populations, but no prior study has performed a multi-ancestry meta-analysis of genome-wide association studies (meta-GWAS) for this trait. We aimed to identify common genetic loci associated with asthma exacerbations across diverse populations and to assess their functional role in regulating DNA methylation and gene expression.MethodsA meta-GWAS of asthma exacerbations in 4989 Europeans, 2181 Hispanics/Latinos, 1250 Singaporean Chinese, and 972 African Americans analyzed 9.6 million genetic variants. Suggestively associated variants (p ≤ 5 × 10-5 ) were assessed for replication in 36,477 European and 1078 non-European asthma patients. Functional effects on DNA methylation were assessed in 595 Hispanic/Latino and African American asthma patients and in publicly available databases. The effect on gene expression was evaluated in silico.ResultsOne hundred and twenty-six independent variants were suggestively associated with asthma exacerbations in the discovery phase. Two variants independently replicated: rs12091010 located at vascular cell adhesion molecule-1/exostosin like glycosyltransferase-2 (VCAM1/EXTL2) (discovery: odds ratio (ORT allele ) = 0.82, p = 9.05 × 10-6 and replication: ORT allele = 0.89, p = 5.35 × 10-3 ) and rs943126 from pantothenate kinase 1 (PANK1) (discovery: ORC allele = 0.85, p = 3.10 × 10-5 and replication: ORC allele = 0.89, p = 1.30 × 10-2 ). Both variants regulate gene expression of genes where they locate and DNA methylation levels of nearby genes in whole blood.ConclusionsThis multi-ancestry study revealed novel suggestive regulatory loci for asthma exacerbations located in genomic regions participating in inflammation and host defense.
| S-EPMC9671132 | biostudies-literature